RECURSIVE COGNITIVE ARCHITECTURE ASSESSMENT: QUANTITATIVE FRAMEWORK FOR META-REASONING EVALUATION IN LARGE LANGUAGE MODELS
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https://zenodo.org/doi/10.5281/zenodo.18155670
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资源简介:
This dataset presents a complete experimental protocol for evaluating recursive and meta-cognitive capabilities in language models. It includes structured six-phase dialogues, quantitative metrics of coherence (82.3%), recursive depth (4.5 layers), and systemic boundary analysis, with validation tools and replication protocols for AI systems evaluation research.
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Zenodo创建时间:
2026-01-05



